<code>Fro</code> returns the Frobenius norm between a Bayesian network and its update after parameter variation.

An implementation of sensitivity and robustness methods in Bayesian networks in R. It includes methods to perform parameter variations via a variety of co-variation schemes, to compute sensitivity functions and to quantify the dissimilarity of two Bayesian networks via distances and divergences. It further includes diagnostic methods to assess the goodness of fit of a Bayesian networks to data, including global, node and parent-child monitors. Reference: M. Leonelli, R. Ramanathan, R.L. Wilkerson (2022) <doi:10.1016/j.knosys.2023.110882>.

Manuele Leonelli

bnmonitor

An Implementation of Sensitivity Analysis in Bayesian Networks

Ramsiya Ramanathan

Rachel Wilkerson

Fro function

<dl><dt>x</dt>
<dd>object of class <code>GBN</code> or <code>CI</code>.</dd>
<dt>...</dt>
<dd>parameters specific to the class used.</dd></dl>

Arguments

Frobenius norm — Fro

<dl>

<dt>x</dt>
<dd>object of class <code>GBN</code> or <code>CI</code>.</dd>


<dt>...</dt>
<dd>parameters specific to the class used.</dd>

</dl>

Data Engineering and BI courses are free this week!

Fro: Frobenius norm

Description

Usage

Value

Arguments

Details

See Also